Acupoint selection rules for acupoint application in lung diseases in the post-epidemic era
Journal Title: TMR Integrative Medicine - Year 2022, Vol 6, Issue 2
Abstract
Objective: To summarize the rules of acupoint selection of acupoint application to prevent and treat lung diseases under the background the post-epidemic era using data-mining technology. Method: The CNKI, Wanfang database, and VIP database were searched for clinical study articles on lung diseases treated by acupoint application published in the past 5 years. Data-eligible papers were extracted to establish a database of acupoint application for lung disease using Microsoft Excel 2019, with the goal of analyzing the frequency of acupoints, acupoint-meridian association, acupoint-location association, specific acupoint frequency, and cluster analysis. Association rules, consisting of acupoints with an application frequency of ³ 10, were devised by the Apriori algorithm to explore the correlation between acupoint groups and to analyze the rules of the compatibility of acupoint prescriptions. Results: A total of 229 eligible papers met our inclusion criteria. Forty-seven acupoints were applied, for a total frequency of acupoints of 1,035 times. Among these, acupoints for lung diseases were primarily distributed in the back-and-waist and chest-and-abdomen areas. From the analysis of the association rules, we obtained four groups of acupoint association rules based on acupoint clusters with a frequency ³ 10 and found that Feishu (BL 13), Tiantu (CV 22), Dazhui (GV 14), Dingchuan (EX-B1), and Danzhong (CV 17) constitute the core acupoints of prescriptions for clinical acupoint application to prevent and treat lung diseases. Conclusion: It is clearly shown that the core acupoints are relatively concentrated and that the selected acupoints were mainly locally selected, which could be a matching reference for the long-term prevention and treatment of lung diseases, including COVID-19.
Authors and Affiliations
An-Hong Dai, Chun-Hong Luo, Yi-Hao Zhou, Gan Huang, Zhi-Lin Huang, Xue-Lian Zhang, Mei-Fang Liu, Jing Shi, You-Long Xiong
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